Systems and methods for chirp linearization using external reflector(s) as a reference reflector

ABSTRACT

Disclosed herein are systems and methods for linearizing frequency chirp in a frequency-modulated continuous wave (FMCW) coherent LiDAR system. Exemplary methods can include generating a continuous wave laser signal having a frequency characteristic, in which the frequency characteristic can include a frequency chirp over a frequency band in at least one period; and receiving a signal based on the generated laser signal. The methods can further include mixing the received signal with a local oscillator signal, the local oscillator signal having the frequency characteristic; determining at least one beat frequency based on the mixed signal; sampling the mixed signal at a rate equal to at least two times the beat frequency; determining a correction signal based on the sampled signal; and applying the correction signal to the laser signal.

TECHNICAL FIELD

The present disclosure features frequency modulated continuous wave(FMCW) coherent LiDAR systems and, in particular, systems and methodsfor linearization of chirp in FMCW coherent LiDAR systems.

BACKGROUND

Some LiDAR systems employ a continuous wave (CW) laser to detect therange and/or velocity of targets. Examples of such systems includefrequency modulated continuous wave (FMCW) coherent LiDARs.

The foregoing examples of the related art and limitations therewith areintended to be illustrative and not exclusive, and are not admitted tobe “prior art.” Other limitations of the related art will becomeapparent to those of skill in the art upon a reading of thespecification and a study of the drawings.

SUMMARY

Systems and methods for linearization of chirp in LiDAR systems aredisclosed. In one aspect, disclosed herein are methods for linearizingfrequency chirp in a frequency-modulated continuous wave (FMCW) coherentLiDAR system. The methods can include generating a continuous wave lasersignal having a frequency characteristic, in which the frequencycharacteristic can include a frequency chirp over a frequency band in atleast one period; and receiving a signal based on the generated lasersignal. The methods can further include mixing the received signal witha local oscillator signal, the local oscillator signal having thefrequency characteristic; determining at least one beat frequency basedon the mixed signal; sampling the mixed signal at a rate equal to atleast four times the beat frequency; determining a correction signalbased on the sampled signal; and applying the correction signal to thelaser signal.

The above and other preferred features, including various novel detailsof implementation and combination of events, will now be moreparticularly described with reference to the accompanying figures andpointed out in the claims. It will be understood that the particularsystems and methods described herein are shown by way of illustrationonly and not as limitations. As will be understood by those skilled inthe art, the principles and features described herein may be employed invarious and numerous embodiments without departing from the scope of anyof the present inventions. As can be appreciated from foregoing andfollowing description, each and every feature described herein, and eachand every combination of two or more such features, is included withinthe scope of the present disclosure provided that the features includedin such a combination are not mutually inconsistent. In addition, anyfeature or combination of features may be specifically excluded from anyembodiment of any of the present inventions.

The foregoing summary, including the description of some embodiments,motivations therefor, and/or advantages thereof, is intended to assistthe reader in understanding the present disclosure, and does not in anyway limit the scope of any of the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures, which are included as part of the presentspecification, illustrate the presently preferred embodiments andtogether with the generally description given above and the detaileddescription of the preferred embodiments given below serve to explainand teach the principles described herein.

FIG. 1 is a diagram of an exemplary FMCW coherent LiDAR systemconfigured to determine the range and/or speed of a target.

FIG. 2A is a plot of ideal (or desired) frequency chirp as a function oftime in the laser signal and reflected signal. FIG. 2B is a plotillustrating the corresponding ideal beat frequency of the mixed signal.

FIG. 3A is a plot of the ideal frequency chirp in transmitted andreceived signals, as depicted in FIG. 2A, and an example actual signalfrom laser and an example realized or actual reflected signal. FIG. 3Bis a plot illustrating the corresponding beat frequency of the actualmixed signal.

FIG. 3C is a diagram of various methods and systems for chirplinearization.

FIG. 4 is a flowchart of an exemplary method for chirp linearization byoversampling in FMCW coherent LiDAR systems.

FIGS. 5A-5B are diagrams of embodiments of a coherent LiDAR systemconfigured for chirp linearization via oversampling. FIG. 5C is adiagram of an embodiment of a modulator in the coherent LiDAR system ofFIG. 5B. FIG. 5D is a diagram of an embodiment of a reference reflectorin the LiDAR system of FIG. 5B.

FIGS. 6A-6B are plots of a comparison to the exemplary short DFTs and aplot of the frequency output of the short DFTs as a function of timeoverlaid on actual beat frequency. FIG. 6C is plot illustrating theapplication of error correction to a laser drive signal.

FIG. 7 is a flowchart of an exemplary method for chirp linearizationwith two CW lasers in FMCW coherent LiDAR systems.

FIGS. 8A-8B are diagrams of embodiments of a coherent LiDAR systemconfigured for chirp linearization via the two CW lasers.

FIG. 9 are plots depicting the processing of laser signals from lasersaccording to exemplary method of FIG. 7 .

FIG. 10 is a flowchart of an exemplary method for chirp linearizationusing the partial FOV as the reference reflector in FMCW coherent LiDARsystems.

FIG. 11 is an embodiment of a coherent LiDAR system configured for chirplinearization via the partial field-of-view (FOV) reference reflector.

FIG. 12A is a diagram of the scanner total FOV including the targetdetection FOV and the reference reflection surface. FIG. 12B is adiagram illustrating the interleaving of reference reflection withtarget reflection during an example scan.

FIG. 13 is a flowchart of an exemplary method for chirp linearizationusing the inline partial reflector as reference reflector in FMCWcoherent LiDAR systems.

FIG. 14A is a diagram of an embodiment of a coherent LiDAR systemconfigured for chirp linearization via partial reflector.

FIGS. 15A-15B are plots providing the respective frequencies of lasersignal, reference reflector signal, and the target reflected signal fromthe target as a function of time.

FIGS. 16A-16B are diagrams of various examples of externally positionedreference reflectors relative to a LiDAR system.

FIG. 17 is a diagram of an example of two reference reflectorspositioned at two respective locations relative to the LiDAR system.

FIG. 18 is a diagram of an exemplary hardware and software systemsimplementing the systems and methods described herein.

While the present disclosure is subject to various modifications andalternative forms, specific embodiments thereof have been shown by wayof example in the drawings and will herein be described in detail. Thepresent disclosure should be understood to not be limited to theparticular forms disclosed, but on the contrary, the intention is tocover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the present disclosure.

DETAILED DESCRIPTION

Systems and methods for linearization of chirp in coherent LiDAR systemsare disclosed. Range (e.g., distance) and/or velocity measurements infrequency modulated continuous wave (FMCW) coherent LiDAR may rely onlinear chirp. In particular, the resolution of the range and/or velocitymeasurements can be affected by chirp linearity. As described in furtherdetail below, various exemplary systems and methods may linearize chirpin FMCW coherent LiDAR systems by one or more of the followingtechniques:

-   -   (i) oversampling;    -   (ii) use of two CW lasers; or    -   (iii) use of a reference reflector, e.g., a partial        field-of-view (FOV), a partial reflector, or an externally        positioned reflector.

One or more exemplary systems and methods for chirp linearization inFMCW coherent LiDAR systems may be employed by autonomous orsemi-autonomous vehicles, including passenger vehicles, industrialrobots, aerial vehicles, underwater vehicles, etc. for the detection ofobjects and/or navigation through space. Note that the followingdescription of the exemplary LiDAR systems and methods may be in thecontext of autonomous vehicles but it is understood that the sameprinciples can be applied to other applications and contexts employingobject detection and/or navigation.

Overview of FMCW Coherent LiDAR Systems

FIG. 1 illustrates an exemplary FMCW coherent LiDAR system 100configured to determine the range and/or speed of a target. LiDAR system100 includes a laser 102 configured to produce a laser signal which isfed into a splitter 104. The laser is “chirped” (e.g., ramped up, rampeddown, etc.) such that the laser frequency is changed with time over afrequency band. In various embodiments, the laser frequency is chirpedquickly such that multiple phase angles are attained. Note that someFMCW LiDAR systems can be configured to detect velocity (both magnitude(speed) and direction) of the movement of a target.

Note that laser chirping is beneficial for range (distance) measurementsof the target. In comparison, Doppler frequency measurements aretypically used for target velocity. Resolution of distance can depend onthe bandwidth size of the chirp frequency band such that greaterbandwidth corresponds to finer resolution, according to the followingrelationships:

${{Range}{resolution}:\Delta R} = {\frac{c}{2{BW}}\left( {{given}a{perfectly}{linear}{chirp}} \right)}$${{Range}:R} = \frac{f_{Bear}cT_{ChirpRamp}}{2{BW}}$where c is the speed of light, BW is the bandwidth size of the chirpedlaser signal, f_(Beat) is the beat frequency (as discussed furtherbelow), and T_(ChirpRamp) is time for the up-ramp portion of the chirpedlaser. For example, for a distance resolution of 1.9 cm, a frequencybandwidth of 8 GHz is used. A linear chirp can be an effective way tomeasure range and range accuracy can depend on the chirp linearity. Insome instances, when chirping is used to measure target range, there maybe range and velocity ambiguity. In particular, the reflected signal formeasuring velocity (e.g., via Doppler) may affect the measurement ofrange. Therefore, some exemplary FMCW coherent LiDAR systems may rely ontwo measurements having different slopes (e.g., negative and positiveslopes) to remove this ambiguity. The two measurements having differentslopes may also be used to determine range and velocity measurementssimultaneously.

The positive slope (“Slope P”) and the negative slope (“Slope N”) (alsoreferred to as positive ramp and negative ramp, respectively) can beused to determine range and/or velocity. In some instances, referring toFIGS. 2A-2B, when the positive and negative ramp pair is used to measurerange and velocity simultaneously, the following relationships areutilized:

${{Range}:R} = \frac{{cT}_{ChirpRamp}\frac{\left( {f_{{beat}\_ P} + f_{{beat}\_ N}} \right)}{2}}{2{BW}}$${{Velocity}:V} = \frac{\lambda\frac{\left( {f_{{beat}\_ P} - f_{{beat}\_ N}} \right)}{2}}{2}$where f_(beat_P) and f_(beat_N) are beat frequencies generated duringpositive (P) and negative (N) slopes of the chirp 202 respectively and λis the wavelength of the laser signal.

In various embodiments, the laser frequency is chirped as linearly aspossible. For example, the chirp is generated up and/or down withconstant slope, which may be referred to as triangle chirp. Other typesof chirp include sawtooth, sinusoidal, etc. However, as discussed below,the linearity of chirp may be challenging to achieve due to the thermaldynamics and/or charge saturation effects of the laser 102. Forinstance, controlled linear chirping may be difficult to achieve innarrow linewidth coherent lasers by direct modulation and, in somecases, may require external modulation of the laser 102. However, anexternal modulator can add loss, complexity, cost, and/or footprint(increased size) to the LiDAR system. Further, even with externalmodulation, chirp characteristics may suffer from non-linearities due toa non-ideal drive signal and/or modulator device characteristics. Theexemplary systems and methods described herein address this challenge ofchirp linearization.

Referring again to FIG. 1 , splitter 104 provides a first split lasersignal Tx₁ to a direction selective device 106, which forwards thesignal Tx₁ to a scanner 108. The scanner 108 uses the first laser signalTx₁ to transmit light and receive reflections back from the target 110.The reflected signal Rx is passed back to the direction selective device106. The second laser signal Tx₂ and reflected signal Rx is provided toa coupler (also referred to as a mixer) 112. The second laser signal Tx₂is used as a local oscillator (LO) signal and mixed with the reflectedsignal Rx. The mixer 112 is configured to mix the reflected signal Rxwith the local oscillator signal LO to generate a beat frequencyf_(beat). The mixed signal with beat frequency f_(beat) is provided to adifferential photodetector 114 configured to produce a current based onthe received light. The current is converted to voltage by atransimpedance amplifier (TIA) and fed to an analog-to-digital converter(ADC) 116 configured to convert the analog signal to digital samples forthe target detection stage 118. Stage 118 is configured to generate therange and/or speed of the target 110 based on the digital sampled signalwith beat frequency f_(beat).

FIG. 2A is a plot of ideal (or desired) frequency chirp as a function oftime in the laser signal Tx (e.g., signal Tx₂), depicted in solid line202, and reflected signal Rx, depicted in dotted line 204. As depicted,the ideal Tx signal has a positive linear slope between time t₁ and timet₃ and a negative linear slope between time t₃ and time t₆. Accordingly,the ideal Rx signal returned with a time delay t_(d) of approximatelyt₂-t₁ has a positive linear slope between time t₂ and time t₅ and anegative linear slope between time t₅ and time t₇.

FIG. 2B is a plot illustrating the corresponding ideal beat frequencyf_(beat) 206 of the mixed signal Tx₂×Rx. Note that the beat frequencyf_(beat) 206 has a constant value between time t₂ and time t₃(corresponding to the overlapping up-slopes of signals Tx₂ and Rx) andbetween time t₅ and time t₆ (corresponding to the overlappingdown-slopes of signals Tx₂ and Rx).

However, actual chirping is not as linear or not completely linear as inthe ideal cases illustrated in FIGS. 2A-2B. This nonlinearity may causeserious errors in its measurements and/or lead to missing a targetaltogether. FIG. 3A is a plot 300 a of the ideal frequency chirp inlaser signal Tx₂ (solid line 202) and return signal Rx (dotted line204), as depicted in FIG. 2A, and an example realized (or actual) signalTx₂ (solid line 302) from laser 102 and an example realized (or actual)reflected signal Rx (dashed line 304). As illustrated, the chirp in theactual signal 302 has a roughly similar sawtooth shape to the idealsignal 202 but the slope of actual signal 302 between time t₁ and timet₃ is not as linear as the slope of signal 202. Analogously, the shapeof the actual reflected signal 304 tracks the shape of the actual signalTx 302 and therefore lacks an entirely linear slope.

FIG. 3B is a plot illustrating the corresponding beat frequency 306 ofthe actual mixed signal Tx₂×Rx. Similarly, the actual beat frequency 306strays from ideal or desired beat frequency 206, making accurate and/orprecise measurements of range difficult to attain.

Accordingly, various systems and methods are discussed below for thelinearization of chirp in coherent LiDAR systems. Referring to FIG. 3C,linearization of chirp 308 can include:

-   -   Systems and methods for chirp linearization by oversampling        (refer to methods 400 and systems 500);    -   Systems and methods for chirp linearization using two continuous        wave (CW) lasers (refer to methods 700 and systems 800);    -   Systems and methods for chirp linearization using partial        field-of-view (FOV) as a reference reflector (refer to methods        1000 and systems 1100); and/or    -   Systems and methods for chirp linearization using a partial        reflector as a reference reflector (refer to methods 1300 and        systems 1400).    -   Systems and methods for chirp linearization using external        reflector(s) as a reference reflector (refer to systems 1600 a,        1600 b).        As illustrated, linearization of chirp 308 can be achieved by        combining one or more of the above systems and methods. In some        embodiments, chirp linearization by oversampling can be combined        with one or more of: (i) linearization using two CW lasers; (ii)        linearization using partial field-of-view (FOV) as a reference        reflector; or (iii) linearization using reflected signals from a        partial reflector.

Linearization of Chirp by Oversampling

In some embodiments, an FMCW coherent LiDAR system may leverage afeedback mechanism to control chirp linearization. For instance, thefeedback mechanism can include oversampling of the mixer output toenable time-resolved frequency measurement. This method can includechirping using direct frequency modulation of the laser 102 or using anexternal modulator.

FIG. 4 is a flowchart of an exemplary method 400 for chirp linearizationby oversampling in FMCW coherent LiDAR systems. FIGS. 5A-5B illustratetwo alternative embodiments of a coherent LiDAR system 500 a, 500 b(collectively referred to as 500) configured for chirp linearization viaoversampling. FIG. 5C illustrates an alternative implementation of anintegrated laser and modulator in the coherent LiDAR system 500 b. FIG.5D illustrates an alternative implementation of a reference reflector inthe LiDAR system 500 b. For the sake of clarity and conciseness, FIGS.4-5D are discussed together below. Note that coherent LiDAR systems 500may share one or more components and/or configuration similarities withsystem 100 and, accordingly, discussion of like elements will not berepeated here.

In step 402 of exemplary method 400, as described above, the lasersignal Tx is generated by laser 102. The laser signal Tx has a frequencythat is chirped (e.g., ramped up and ramped down) over a frequency band.In step 404, a reflected signal of the target is received by the scanner108 and provided to the mixer 112 with an LO signal (e.g., Tx2). Themixed signal can be sampled by the ADC 116. In step 406, the sampledsignal is used by the processing unit 118 to determine one or more beatfrequencies in the return signal. In particular, the processing unit 118can execute one or more discrete Fourier transforms (DFTs) to determinethe beat frequencies.

In FIG. 6A, plots 300 a, 300 b are provided in comparison to theexemplary short DFTs 602 and a plot 604 of the frequency output of theshort DFTs as a function of time overlaid on actual beat frequency 306.Referring back to the exemplary LiDAR system 100, one large DFT (e.g.,with time window size Tw1+Tw2) or two large DFTs (e.g., time window sizeTw1 and Tw2) can be performed per pixel by the processing unit 118 todetermine one or more beat frequencies present in the return signal fromthe target 110. These beat frequencies can be used to determine rangeand/or velocity of the target 110. In some embodiments, the processingunit 118 can determine the maximum beat frequency in the return signal.The maximum beat frequency may be determined by the longest range and/orfastest speed that system 500 a is configured to measure. In someembodiments, the sampling rate of the ADC 116 is selected such that eachDFT has the minimum number of sample points to provide the desired rangeresolution.

However, for chirp linearization in the exemplary step 408, the ADC 116can be configured to oversample the mixed signal, e.g., at a rategreater than the beat frequency (e.g., at least two times, at leastthree times, at least four times, at least five times, at least tentimes, at least 15 times, at least 20 times, at least 30 times, at least50 times, etc.). In some embodiments, the ADC 116 is configured tooversample the maximum beat frequency (e.g., at least two times, atleast three times, at least four times, at least five times, etc. themaximum beat frequency). For example, the ADC 116 may sample the mixedsignal at a rate equal to at least ten times the maximum beat frequency.Note that the oversampling factor can depend on the maximum frequencycontent of the nonlinearity that the system is being configured tocompensate. As illustrated in plot 600, the processing unit 118 can beconfigured to perform short DFTs 602 to assess a beat frequency in timeintervals shorter than time window Tw1 and/or time window Tw2. Forinstance, dividing time window Tw1 or Tw2 in ten or more intervals canbe preferable to attain a fine resolution frequency measurement. In someembodiments, DFTs 602 can be executed on disjoint data blocksback-to-back, on adjacent data blocks, and/or on overlapping data blocksto attain greater resolution (e.g., a greater number of correctionpoints per time window). In some embodiments, the short DFTs may besliding DFTs with overlap, resulting in more correction points and asmoother drive signal for the laser 102.

In step 410, the digitized signal from the ADC 116 is provided to aprocessing stage 504 configured to process the digitized signal usingtime-resolved sliding frequency analysis to determine an error signal(also referred to as the correction signal). As described in furtherdetail below, the error signal can include the amount with which thefrequency of the actual signal 306 deviates from the ideal signal 206.Referring to plot 604, the expected frequency 608 (e.g., the averagefrequency) over time window Tw1 and/or Tw2 can be used to determine theerror, which in turn can be used correct the modulation drive ramp usedto control the frequency of the laser 102. Accordingly, the method 400can include determining the expected frequency 608 over one or more timewindows. Additionally or alternatively, the expected value of the beatfrequency from reference reflection surface 502 (coupled to the outputof the scanner 108 in system 500 a or 500 b) may be used to determinethe error. In some embodiments, the correction signal can be addedrepeatedly, continuously, periodically, or intermittently in a feedbackloop during live operation in field (in-situ) and/or run as a separatecalibration procedure at the start-up of the LiDAR system. For example,the feedback loop can be executed every cycle or after every N number ofcycles (e.g., to save power and/or process time) in situ.

In step 412, the processed signal and a desired frequency ramp fromgenerator 506 are provided to an error stage 508 to generate acorrection (error) signal. In some embodiments, the desired frequencyramp is stored in a memory and accessed for use. In some embodiments, anaverage measured value (e.g., expected frequency 608) can be used todetermine the desired frequency ramp. In particular, the error stage 508is configured to compare the processed signal to the desired linearbehavior of the ideal chirp.

FIG. 6B illustrates error calculation and the correction of modulationdrive to linearize the frequency modulation of laser 102. During errorcalculation, error signals e1, e2, . . . ek are determined forrespective short DFT outputs 606. In various embodiments, error signalcan be expressed as the difference between the expected frequencyf_(expected) and the measured frequency f_(measured):e _(k) =f _(expected) −f _(measured)In some embodiments, each error signal is the deviation (e.g., frequencydifference) between the mean frequency 608 and the respective short DFToutput. In some embodiments, the error signal is the absolute value ofthe deviation from a reference signal (e.g., using the second CW lasersignal as the reference signal, as described further below). Asillustrated in plot 612, these error signals e1, e2, . . . ek areapplied to the modulation drive signal 614 to form the correctedmodulation drive signal 616.

Referring to exemplary system 500 a, the correction signal and desiredfrequency ramp can be provided to a frequency modulation stage 510.Stage 510 adds the correction signal to the desired frequency ramp toform a corrected drive signal to drive the laser 102 in the next cycle,as described in further detail below). In some embodiments, themodulation drive signal to control the chirp or laser 102 is determinedand/or updated according to the following relationship:modulation_drive[k,t=n+1]=modulation_drive[k,t=n]+μ*Error[k,t=n]where k is the index for location on the ramp, n is ramp index, and μ isthe feedback loop gain. The feedback loop gain can be used to controlhow aggressively the correction is applied to the laser drive signal.For instance, a higher value of μ causes faster convergence but has alarger fluctuation around the final value. Conversely, a lower value ofμ causes slower convergence but has a smaller fluctuation around thefinal value.

In some embodiments, the correction is applied to the laser drive signalas soon as it is determined because, in some cases, it may be feasibleto apply the correction with little or no delay. In some embodiments, adelay block is included to apply a delay to the error correction. Forinstance, the delay block 509 a (optionally connected to controller 511)may be positioned between the error stage 508 and the frequencymodulation stage 510. In another example, the delay block 509 b(optionally connected to controller 511) may be positioned between theanalysis block 504 and the error block 508. The delay block (509 a or509 b, collectively referred to as 509) and/or controller (511) can beconfigured such that the correction is applied at the appropriate timesin the cycle (e.g., at the same or approximately the same position alongthe rising or falling slopes of the chirped laser signal, as discussedbelow).

In some implementations, the behavior in the error in each slope of thechirped laser signal is fairly deterministic. For instance, the error inthe rising slope of the laser signal is similar to the error insubsequent rising slopes of the laser signal. FIG. 6C illustrates anexample laser drive signal 618 that is corrected over one or morecycles. The laser drive signal 618 can be oversampled (refer to indexi). These samples can be binned (also referred to as buckets) with indexk. Executing DFTs over these bins can produce frequency for each bin k.These bins k may be configured adjacent to one another (refer to bins622) or overlapping with one another (refer to bins 624).

In some embodiments, the error correction signal can be determined onone or more slopes and applied to one or more future slopes. Therefore,indexing over the slopes with index n, correction to slope n+1, n+2,etc. can be made with information from slopes n, n−1, etc. For example,the error correction signal is determined for slope 1P of the laserdrive signal 618 and is applied (with a delay) to slopes 2P, 3P, 4P,etc. In another example, the error correction signal is determined forslopes 1P and 2P and is applied (with a delay) to slopes 3P, 4P, etc.Note that the delay may be imposed by the delay block 509. For example,referring to error e_(k) for a given sample point on laser drive signal618, the correction 620 is applied in the same position along parallelslopes (e.g., slopes 2P and 3P). In some embodiments, a controller 511that is connected to the delay block 509 can be configured to adjust thedelay applied to the error correction. The controller 511 may beconfigured to keep track of the points on the slopes that are beingcorrected.

In some embodiments, the frequency modulation may be applied to thelaser 102 via the laser bias (gain stage) 512. In exemplary system 500b, the correction signal at stage 514 may be provided to a frequencymodulation generator 516. The generator 514 may send the correctedmodulation signal to modulator 518. In other embodiments, the frequencymodulation may be applied via a separate electrode, e.g., a phasemodulation electrode of the laser 102. For example, laser 102 may becoupled to a phase modulation electrode to control the phase of lightwithin the cavity the laser 102. Frequency modulation may be based onthe phase modulation of the light. In some embodiments, the modulator518 and splitter 104 may be on the same integrated circuit (IC) (e.g.,monolithic chip), may be co-packaged, or on separate ICs.

The exemplary method 400 for linearizing chirp may be performed in afactory (e.g., before deployment) or in situ (e.g., during operation).In some embodiments, this method can be applied to direct frequencymodulation of laser 102 or to one or more external modulators (e.g.,modulator 518) coupled to laser 102. Note that components or functions116, 118, 504, 506, 508, and/or 510 may be part of or enabled by one ormore processors, one or more computing systems, one or more serversystems, etc.

In some embodiments, the exemplary method 400 and/or exemplary system500 can utilize a reference delayed signal to generate the error signalfor correction. As discussed further below, such a reference delayedsignal may be obtained using a built-in reference reflection within theLiDAR system (e.g., refer to method 1000 and system 1100), a reflectionfrom the front face of the launching optics (e.g., refer to method 1300and system 1400), and/or a reflection from the target 110.

Linearization of Chirp Using Two Continuous Wave Lasers

In some embodiments, chirp linearization can be attained with the use ofa second laser (e.g., a second continuous wave (CW) laser). Thefollowing describes exemplary systems and methods for linearizing chirpin FMCW coherent LiDAR systems with two CW lasers (e.g., one unmodulatedCW laser and one FMCW laser).

FIG. 7 is a flowchart of an exemplary method 700 for chirp linearizationwith two CW lasers in FMCW coherent LiDAR systems. FIGS. 8A-8Billustrate two alternative embodiments of a coherent LiDAR system 800 a,800 b (collectively referred to as 800) configured for chirplinearization via the two CW lasers. For the sake of clarity andconciseness, FIGS. 7-8B are discussed together below. Note that coherentLiDAR systems 800 may share one or more components and/or configurationsimilarities with systems 100, 500 a, or 500 b and, accordingly,discussion of like elements will not be repeated here.

FIG. 8A illustrates a coherent LiDAR system 800 a. In step 702 ofexemplary method 700, a first laser signal is generated by laser 802 aand provided to a splitter 804 a. The splitter 804 a provides a firstchirped laser signal to another splitter 804 b for directing to target110 (as discussed in detail above). Splitter 804 a provides a secondchirped laser signal (e.g., having the same characteristics of the lasersignals Tx1, Tx2). to a mixer 806. In step 704, laser 802 b isconfigured to generate a second laser signal in CW mode. The mixer 806is configured to receive the second laser signal from laser 802 b. Instep 706, the chirped laser signal is mixed with the CW laser signal.Accordingly, the output of mixer 806 is used in generating a correctionsignal for LiDAR system 800 a (via path 810). The mixed signal beats atthe difference in frequency between two laser signals and is provided toanother ADC 808. Note that components or functions 116, 118, 504, 506,508, 510, and/or 808 may be part of or enabled by one or moreprocessors, one or more computing systems, one or more server systems,etc.

FIG. 8B illustrates an alternative embodiment of LiDAR system 800 b. Inparticular, a single splitter 804 a provides a chirped signal to a mixer806, which mixes the chirped signal with the CW signal from laser 802 b.The output of mixer 806 is provided as an LO signal to mixer 112. Notethat, in LiDAR system 800 b, mixer 112 also receives the reflectionsignal Rx and is used for target detection (e.g., at stage 118), therebycreating a single channel for both detection and correction. The outputof mixer 112 is used to determine the beat frequency and so forth, asdescribed for exemplary system 500 a. Note that LiDAR system 800 b canbe operated in at least the following modes:

-   -   Mode 1—Calibration mode. In calibration mode, the target        reflection can be blocked. For example, the scanner 108 can be        oriented inward and/or away from a location of a target. By        being oriented inward, the scanner 108 absorbs the light from        the laser 802 a. Because no target reflections are received, the        system 800 b is configured to generate a correction signal to        linearize the chirp.    -   Mode 2—Operational mode. In operational mode, the scanner 108        operates normally to detect target reflections. Laser 802 b can        be turned off so no correction signals are being generated        during Mode 2.        In the above embodiment, LiDAR system 800 b may be in Mode 1        before Mode 2 (e.g., before each instance of measuring target        range and speed). In some embodiments, LiDAR system 800 b may be        in Mode 1 for testing after assembly (e.g., at the manufacturing        stage, in a factory, etc.). In some embodiments, LiDAR system        800 b may be in Mode 1 at the starting of and/or powering up of        LiDAR system 800 b. In some embodiments, LiDAR system 800 b may        switch between Mode 1 and Mode 2 (e.g., at predetermined        intervals). For example, system 800 b may switch between Modes 1        and 2 every second, every 5 seconds, every 10 seconds, every 30        seconds, every minute, etc. In some embodiments, LiDAR system        800 b may enter Mode 1 upon a trigger, e.g., based on the system        temperature (e.g., when the temperature changes by more than 1        degree, 2 degrees, 3 degrees, 5 degrees, etc.) or on a change in        power level of the system 800 b.

It is understood that other variations of systems 800 a, 800 b can beimplemented to achieve linear chirp. For example, splitters 804 a and804 b of system 800 a can be combined into a single splitter. In anotherexample, for a multi-channel laser (e.g., at laser 802 a) in whichmultiple spatial channels are realized by splitting the output of laser802 a, a single CW laser 802 b can be employed. In another example,laser 802 a and laser 802 b may be part of a single laser device (e.g.,having two channels).

FIG. 9 illustrates the processing of laser signals from lasers 802 a,802 b according to exemplary method 700. Plot 900 illustrates the actualfrequency 302 of laser 802 a and constant frequency 902 of laser 802 b.Plot 904 illustrates the beat frequency 906 of mixed signals from laser802 a and laser 802 b. Note that beat frequency of mixed signal 906 is atime-shifted version of actual frequency 302 (e.g., by the frequency ofCW laser 802 b).

This beat frequency may be determined by time-resolved frequencymeasurements via DFTs (e.g., at time-resolved frequency analysis stage504). To execute the time-resolved DFTs, in step 708, the mixed signalcan be oversampled (as described in detail above). Referring to FIG. 9 ,short DFTs 910 in plot 908 are illustrated with respect to timeincrements t. In some embodiments, DFTs can be executed on disjoint datablocks back-to-back, on adjacent data blocks, and/or on overlapping datablocks to attain greater resolution (e.g., a greater number ofcorrection points per time window). Example DFTs 910 are depicted asadjacent but disjoint data blocks. In some embodiments, the DFTs 910 maybe sliding DFTs with overlap, resulting in more correction points and asmoother drive signal for the laser 802 a.

In step 710, one or more error signals e1, e2, . . . ek (correctionsignals) can be determined by comparing measured beat frequency 906 withdesired linear chirp 202. In some embodiments, a linear fit is used onthe measured beat frequency (e.g., a linear fit for the positive slopeand another fit for negative slope). The error from desired slope 202 isdetermined as function of location on the frequency slope. In someembodiments, the frequency of the second CW laser signal 802 b is usedas the reference signal. The absolute value of the deviation from thereference signal may be used to determine the error in the chirped lasersignal. For example, the chirped laser signal 802 a varies in frequencybetween 190-191 THz and the CW laser signal 802 b has a constantfrequency at 100 THz. In an example where the measured frequency is190.0008 THz, the error correction would be the absolute value of thedifference 190 THz−190.0008 THz=0.0002 THz.

At step 712, these error signals at stage 508 can be used to correct thefrequency modulation control at stage 510 to drive laser 802 a. In plot914, the error signals e1, e2, . . . ek are applied to a modulationsignal 916 to form a corrected modulation signal 918. In someembodiments, the modulation drive signal to control the chirp of laser802 a is determined and/or updated according to the followingrelationship:modulation_drive[k,t=n+1]=modulation_drive[k,t=n]+μ*error[k,t=n]where k is the index for location on the ramp, n is time ramp index, andμ is the feedback loop gain. The feedback loop gain can be used todetermine how aggressively the correction is applied to the laser drivesignal. For instance, a higher value of μ causes faster convergence buthas a larger fluctuation around the final value. Conversely, a lowervalue of μ causes slower convergence but has a smaller fluctuationaround the final value.

This feedback correction can be executed repeatedly to minimize theerror and/or track near the minimum error. For example, this correctioncan be executed repeatedly, continuously, periodically, orintermittently in a feedback loop during live operation in field (insitu) and/or executed as a separate calibration procedure at start-up ofthe LiDAR system. For example, the feedback loop can be executed everycycle or after every N number of cycles (e.g., to save power and/orprocess time) in situ. In some embodiments, the correction signal can beapplied to direct frequency modulation of laser 802 a or to one or moreexternal modulators. The method 700 may incorporate oversampling, e.g.,as described in method 400.

Linearization of Chirp Using Partial Field-of-View (FOV) as ReferenceReflector

In some embodiments, chirp linearization can be attained with the use ofa reference reflector. In some cases, the reference reflector can be thescanner's partial FOV. The following describes exemplary systems andmethods for linearizing chirp in FMCW coherent LiDAR systems using thepartial FOV as the reference reflector.

FIG. 10 is a flowchart of an exemplary method 1000 for chirplinearization using the partial FOV as the reference reflector in FMCWcoherent LiDAR systems. FIG. 11 illustrates an embodiment of a coherentLiDAR system 1100 configured for chirp linearization via the partial FOVreference reflector. For the sake of clarity and conciseness, FIGS.10-11 are discussed together below. Note that coherent LiDAR system 1100may share one or more components and/or configuration similarities withsystems 100, 500 a, 500 b, 800 a, or 800 b and, accordingly, discussionof like elements will not be repeated here.

In step 1002 of exemplary method 1000, the laser signal Tx is generatedby laser 102. The laser signal Tx has a frequency that is chirped (e.g.,ramped up, ramped down, etc.). In step 1004, a reflected signal of thetarget is received by the scanner 1102. In this embodiment, a portion ofthe total FOV of the scanner 1102 can be allocated to attain a referencereflection from surface 1104. During an FOV scan, the scanner 1102 candirect the light beam to this region 1104 and receive a referencereflection signal.

Referring to FIG. 12A, the total FOV 1202 of scanner 1102 includes thetarget detection FOV 1204 (which is used to detect targets 110) and thereference reflection surface 1104. In some embodiments, the referencereflection surface 1104 can be semitransparent. A semitransparentreflection surface can reflect a portion of the incident light beam andenable transmission of another portion (e.g., the rest of) the lightbeam. If the transmitted light beam reflects off of the target andreturns to receiver optic (e.g., of scanner 1102), two beat frequenciescan be created. A lower beat frequency can be at a deterministicfrequency based on the distance 1106 from the transmitter optic to thereference reflection surface 1104 (e.g., due to the shorter distancebetween the scanner 1102 and surface 1104). In some embodiments, thereference reflection surface 1104 is in the same enclosure are thescanner 1102. In some embodiments, an optical fiber may be used to buildin greater distance between the scanner 1102 and surface 1104. Thehigher beat frequency can be based on the distance 1108 of thetransmitter optic (e.g., of scanner 1102) to the target 110 (e.g., dueto the longer distance between the scanner 1102 and target 110). Notethat other shapes (e.g., circular, checkered, triangular, etc.) for thereference reflection surface 1104 are within the scope of thisdisclosure. The scanner 1102 can scan with example pattern 1206, whichcan overlap both the target detection FOV 1204 and reference reflectionsurface 1104. Note that other scan patterns (e.g., spiral shape scan,vertical scan, etc.) are within the scope of this disclosure. In someembodiments, the light can be directed in a time-interleaved manner.

Using this reference reflection signal, the exemplary system 1100 canperform error calculation and correct the modulation signal to linearizethe chirp, as described further below. In some embodiments, thelinearization determination is initialized and/or integrated when thescanner pattern 1206 passes over the reference reflection surface 1104.In particular, the error calculation for chirp linearization can beinterleaved as part of the scan 1208. FIG. 12B illustrates theinterleaving of reference reflection with target reflection during anexample scan 1208. In particular, the instances of reference reflection(denoted by ‘R’ in a gray box) is interspersed with the instances oftarget detection (denoted by a white box).

The reflected signal is provided to the mixer 112 with an LO signal. Instep 1006, the mixed signal is used by the ADC 116 to determine one ormore beat frequencies in the return signal. In particular, theprocessing unit 118 can execute one or more DFTs to determine the beatfrequencies according to the time-resolved frequency determinationtechnique discussed above. In some embodiments, the short sliding DFTscan be used. In step 1008, to execute the time-resolved DFTs, the mixedsignal can be oversampled (as described in detail above).

In step 1010, one or more error signals (also referred to as correctionsignals) can be determined, as described in greater detail above. Atstep 1012, these error signals at stage 508 can be used to correct thefrequency modulation control at stage 510 to drive laser 802 a.

In some embodiments, the method 1000 can be used to linearize the chirpof laser 102 and/or used by the external modulator to linearize chirp.The method 1000 may incorporate oversampling, e.g., as described inmethod 400. The method 1000 may be used during operation (in situ).

Linearization of Chirp Using Reflected Signals from Partial Reflector

In some embodiments, chirp linearization can be attained with the use ofa reference reflector, which may include a partial reflector, e.g., theinline facet of a beam-forming optical device of the LiDAR system. Thefollowing describes exemplary systems and methods for linearizing chirpin FMCW coherent LiDAR systems using the partial reflector as thereference reflector.

FIG. 13 is a flowchart of an exemplary method 1300 for chirplinearization using the partial reflector as reference reflector in FMCWcoherent LiDAR systems. FIG. 14 illustrates an embodiment of a coherentLiDAR system 1400 configured for chirp linearization via partialreflector as reference reflector. For the sake of clarity andconciseness, FIGS. 13-14 are discussed together below. Note thatexemplary LiDAR system 1400 may share one or more components and/orconfiguration similarities with systems 100, 500 a, 500 b, 800 a, 800 b,or 1100 and, accordingly, discussion of like elements will not berepeated here.

In step 1302 of exemplary method 1000, the laser signal Tx is generatedby laser 102. The laser signal Tx has a frequency that varies (e.g.,ramped up, ramped down, chirped, etc.). In step 1304, a beam formingoptical device 1404 (also referred to as launching optics) is used toform the light for projecting onto a target 110. The beam formingoptical device 1404 may include a partial reflector to be used areference. In particular, the inline optical facet or the front facet ofthe optical device 1404 can be employed to provide the referencereflection. The lens interface is partially reflecting due to dielectricchange when transiting to free space. This reflection may be sufficientto provide the reflection needed to provide the reference signal.

The reflection from the partial reflector (e.g., the inline opticalfacet of optical device 1404) can be used to determine (e.g., derive,calculate, etc.) a reference signal used to correct the frequencymodulation signal in chirp linearization. Optionally, the device 1404may be coupled to a scanner 1406 with FOV 1408. During operation (oroffline), the optical device 1404 and/or scanner 1102 can direct thelight beam to the target 110 and receive a reference reflection signal.Using this reference reflection signal, the exemplary system 1100 canperform error calculation and correct the modulation signal to linearizethe chirp, as described further below.

Referring to FIG. 15A, plot 1500 provides the respective frequencies oflaser signal Tx 202 (solid line), reference reflector signal 1502(dashed line), and the reflected signal 204 from the target 110 (e.g., astationary target) as a function of time. Note that the referencereflector signal 1502 is delayed in time from the laser signal 202 withtime t_(delay1) and the target reflected signal 204 is delayed in timefrom the laser signal 202 with time t_(delay2). Plot 1504 provides thebeat amplitude (of the DFT outputs) as a function of frequency. Inparticular, the beating 1506 caused by the reference reflector ofoptical device 1404 is at a lower frequency f_(beat_ref) than thebeating 1508 frequency f_(beat_target) caused by the target 110. This isbecause the reference reflector is closer to laser 102 than the target110, therefore causing the chirp waveform to have less time delay. Notethat DFT can clearly separate the beating frequency f_(beat_ref) causedby reference reflector signal 1502 from beating frequencyf_(beat_target) caused by target(s) as they are at differentfrequencies. Using the illustrations of plots 1500 and 1504, therelationships of chirp, range, and velocity are defined as described inthe following.

As shown in FIG. 15B, on the positive (P) and negative (N) ramps (alsoreferred to as “Slope-P” and “Slope-N”, respectively), beating occursdue to a reference reflector and a target (e.g., a moving target).Because the range (location) information about reference reflector isknown, this information is used to determine ideal beat frequencyassociated with the reference reflector. This beat frequency associatedwith reference reflector can be used as the expected frequency todetermine the error for the drive for frequency modulation of the laser.(Beat frequency related to the reference reflector can be separated fromtarget-related beat frequency as DFT by its very nature separates thefrequencies present in its input).

Rangeofreferencereflector:${{R\_ ref}{\_ relector}} = {\frac{{cT}_{ChirpRamp}}{2{BW}} \cdot \left( \frac{f_{{beat}\_ P} + f_{{beat}\_ N}}{2} \right)}$Velocityofreferencereflector:${{V\_ ref}{\_ reflector}} = {\frac{\lambda}{2} \cdot \left( \frac{f_{{beat}\_ P} - f_{{beat}\_ N}}{2} \right)}$Note that range and velocity of the reference reflector provided aboveare with respect to the laser and detector system in the LiDAR system.

In various embodiments, the reference reflector is stationary and at aknown location with respect to the laser and detector system. Becausethe reference reflector is stationary with respect to the laser anddetection system, beat frequencies caused by the reference reflector onpositive and negative ramps are equal, f_(beat_P)=f_(beat_N). In thefollowing, this beat frequency is referred to as f_(beat_ref).

Rangeofreferencereflector:${{R\_ ref}{\_ relector}} = {\frac{{cT}_{ChirpRamp}}{2{BW}} \cdot f_{{beat}\_{ref}}}$Beatfrequencyrelatedtothereferencereflector:$f_{{beat}\_{ref}} = {{\frac{2{BW}}{{cT}_{ChirpRamp}} \cdot {R\_ ref}}{\_ relector}}$This beat frequency associated with reference reflector f_(beat_ref) canbe used as expected frequency to calculate frequency error (e_(k)).

The reference reflector can be within the LiDAR enclosure (e.g.,housing) or it may be positioned externally to the LiDAR enclosure. Notethat, if an external reflector is used, it may be stationary withrespect to the LiDAR system if the LiDAR system is itself stationary.FIGS. 16A-16B illustrate various examples of externally positionedreference reflectors. For example, in FIG. 16A, the LiDAR system 1602may be installed on a post or building 1604 and the reference reflector1606 is positioned externally some distance away from the LiDAR system1602. In FIG. 16B, the reference reflector 1606 may be mounted to samechassis as the LiDAR system 1602 (e.g., on the body of the vehicle 1608on which LiDAR system 1602 is mounted).

In some embodiments, there may be more than one reference reflector thatis used in the systems and methods described herein. If multiplereference reflectors (e.g., placed at different distances or the samedistance away from the LiDAR system) are used, then error signal e_(k)can be an average or weighted sum of error e_(k) calculated using eachreference reflector. FIG. 17 illustrates an example of two referencereflectors 1702 and 1704 positioned at two respective locations relativeto the LiDAR system 1706.

The range and velocity for the target are determined using therelationships outlined above and provided here:

${{Range}:R_{target}} = \frac{{cT}_{ChirpRamp}\frac{\left( {f_{{beat}\_ P} + f_{{beat}\_ N}} \right)}{2}}{2{BW}}$${{Velocity}:V_{target}} = \frac{\lambda\frac{\left( {f_{{beat}\_ P} - f_{{beat}\_ N}} \right)}{2}}{2}$In some embodiments, the correction to the drive signal is determined bycalculating the error in the comparison of the beating frequency 1506caused by reference reflector to its expected value. The expected valuefor beat frequency f_(beat_ref) 1506 may be obtained: (i) based on thelocation of the reference reflector in optics 1404 and/or (ii) based onthe average value (e.g., value 608) in the measurement period (e.g.,time window Tw1 or Tw2).

The reflected signal is provided to the mixer 112 with an LO signal,resulting in a beat frequency. In step 1306, the mixed signal is used bythe ADC 116 to determine one or more beat frequencies in the returnsignal. In particular, the processing unit 118 can execute one or moreDFTs on the sampled signal from ADC 116 to determine the beatfrequencies. In some embodiments, the short sliding DFTs can be used. Instep 1308, to execute the time-resolved DFTs, the mixed signal can beoversampled (as described in detail above).

In step 1310, one or more error signals (also referred to as correctionsignals) can be determined, as described in greater detail above. Atstep 1312, these error signals at stage 508 can be used (e.g., in afeedback loop) to correct the frequency modulation control at stage 510to drive laser 802 a. In some embodiments, the correction loop can becontinuously, intermittently, and/or periodically operated to minimizethe error in the laser chirp.

In some embodiments, the method 1300 can be used to linearize the chirpof laser 102 and/or used by the external modulator to linearize chirp.The method 1300 may incorporate oversampling, e.g., as described inmethod 400. The method 1300 may be used during operation (in situ) oroffline (not in use). For instance, system 1400 can operate in at leastthe following modes:

Mode 1—Calibration (offline state). LiDAR system 1400 can use referencereflector of optics 1404 to calibrate (e.g., generate correctionsignals). In this mode, the system 1400 is not measuring the range orspeed of target 110.

Mode 2—Operational (in situ). LiDAR system 1400 can interleave the useof the reference reflector with the scanning of FOV 1408 (at target110).

In the above embodiment, the system LiDAR system 1400 may be in Mode 1before Mode 2 (e.g., before each instance of measuring target range andspeed). In some embodiments, LiDAR system 1400 may be in Mode 1 fortesting after assembly (e.g., at the manufacturing stage, in a factory,etc.). In some embodiments, LiDAR system 1400 may be in Mode 1 at thestarting of and/or powering up of LiDAR system 1400. In someembodiments, LiDAR system 1400 may enter Mode 1 upon a trigger, e.g.,based on the system temperature (e.g., when the temperature changes bymore than 1 degree, 2 degrees, 3 degrees, 5 degrees, etc.) or on achange in power level of the system 1400.

Hardware and Software Implementations

FIG. 18 is a block diagram of an example computer system 1800 that maybe used in implementing the technology described in this document.General-purpose computers, network appliances, mobile devices, or otherelectronic systems may also include at least portions of the system1800. The system 1800 includes a processor 1810, a memory 1820, astorage device 1830, and an input/output device 1840. Each of thecomponents 1810, 1820, 1830, and 1840 may be interconnected, forexample, using a system bus 1850. The processor 1810 is capable ofprocessing instructions for execution within the system 1800. In someimplementations, the processor 1810 is a single-threaded processor. Insome implementations, the processor 1810 is a multi-threaded processor.The processor 1810 is capable of processing instructions stored in thememory 1820 or on the storage device 1830.

The memory 1820 stores information within the system 1800. In someimplementations, the memory 1820 is a non-transitory computer-readablemedium. In some implementations, the memory 1820 is a volatile memoryunit. In some implementations, the memory 1820 is a nonvolatile memoryunit.

The storage device 1830 is capable of providing mass storage for thesystem 1800. In some implementations, the storage device 1830 is anon-transitory computer-readable medium. In various differentimplementations, the storage device 1830 may include, for example, ahard disk device, an optical disk device, a solid-date drive, a flashdrive, or some other large capacity storage device. For example, thestorage device may store long-term data (e.g., database data, filesystem data, etc.). The input/output device 1840 provides input/outputoperations for the system 1800. In some implementations, theinput/output device 1840 may include one or more of a network interfacedevices, e.g., an Ethernet card, a serial communication device, e.g., anRS-232 port, and/or a wireless interface device, e.g., an 802.11 card, a3G wireless modem, or a 4G wireless modem. In some implementations, theinput/output device may include driver devices configured to receiveinput data and send output data to other input/output devices, e.g.,keyboard, printer and display devices 1860. In some examples, mobilecomputing devices, mobile communication devices, and other devices maybe used.

In some implementations, at least a portion of the approaches describedabove may be realized by instructions that upon execution cause one ormore processing devices to carry out the processes and functionsdescribed above. Such instructions may include, for example, interpretedinstructions such as script instructions, or executable code, or otherinstructions stored in a non-transitory computer readable medium. Thestorage device 1830 may be implemented in a distributed way over anetwork, for example as a server farm or a set of widely distributedservers, or may be implemented in a single computing device.

Although an example processing system has been described in FIG. 18 ,embodiments of the subject matter, functional operations and processesdescribed in this specification can be implemented in other types ofdigital electronic circuitry, in tangibly-embodied computer software orfirmware, in computer hardware, including the structures disclosed inthis specification and their structural equivalents, or in combinationsof one or more of them. Embodiments of the subject matter described inthis specification can be implemented as one or more computer programs,i.e., one or more modules of computer program instructions encoded on atangible nonvolatile program carrier for execution by, or to control theoperation of, data processing apparatus. Alternatively or in addition,the program instructions can be encoded on an artificially generatedpropagated signal, e.g., a machine-generated electrical, optical, orelectromagnetic signal that is generated to encode information fortransmission to suitable receiver apparatus for execution by a dataprocessing apparatus. The computer storage medium can be amachine-readable storage device, a machine-readable storage substrate, arandom or serial access memory device, or a combination of one or moreof them.

The term “system” may encompass all kinds of apparatus, devices, andmachines for processing data, including by way of example a programmableprocessor, a computer, or multiple processors or computers. A processingsystem may include special purpose logic circuitry, e.g., an FPGA (fieldprogrammable gate array) or an ASIC (application specific integratedcircuit). A processing system may include, in addition to hardware, codethat creates an execution environment for the computer program inquestion, e.g., code that constitutes processor firmware, a protocolstack, a database management system, an operating system, or acombination of one or more of them.

A computer program (which may also be referred to or described as aprogram, software, a software application, a module, a software module,a script, or code) can be written in any form of programming language,including compiled or interpreted languages, or declarative orprocedural languages, and it can be deployed in any form, including as astandalone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment. A computer program may, butneed not, correspond to a file in a file system. A program can be storedin a portion of a file that holds other programs or data (e.g., one ormore scripts stored in a markup language document), in a single filededicated to the program in question, or in multiple coordinated files(e.g., files that store one or more modules, sub programs, or portionsof code). A computer program can be deployed to be executed on onecomputer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a communicationnetwork.

The processes and logic flows described in this specification can beperformed by one or more programmable computers executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Computers suitable for the execution of a computer program can include,by way of example, general or special purpose microprocessors or both,or any other kind of central processing unit. Generally, a centralprocessing unit will receive instructions and data from a read-onlymemory or a random access memory or both. A computer generally includesa central processing unit for performing or executing instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto optical disks, or optical disks.However, a computer need not have such devices.

Computer readable media suitable for storing computer programinstructions and data include all forms of nonvolatile memory, media andmemory devices, including by way of example semiconductor memorydevices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks,e.g., internal hard disks or removable disks; and magneto optical disks.The processor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of what may beclaimed, but rather as descriptions of features that may be specific toparticular embodiments. Certain features that are described in thisspecification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable subcombination. Moreover, although features may be describedabove as acting in certain combinations and even initially claimed assuch, one or more features from a claimed combination can in some casesbe excised from the combination, and the claimed combination may bedirected to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Particular embodiments of the subject matter have been described. Otherembodiments are within the scope of the following claims. For example,the actions recited in the claims can be performed in a different orderand still achieve desirable results. As one example, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous. Other steps or stages may be provided,or steps or stages may be eliminated, from the described processes.Accordingly, other implementations are within the scope of the followingclaims.

Terminology

The phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting.

The term “approximately”, the phrase “approximately equal to”, and othersimilar phrases, as used in the specification and the claims (e.g., “Xhas a value of approximately Y” or “X is approximately equal to Y”),should be understood to mean that one value (X) is within apredetermined range of another value (Y). The predetermined range may beplus or minus 20%, 10%, 5%, 3%, 1%, 0.1%, or less than 0.1%, unlessotherwise indicated.

The indefinite articles “a” and “an,” as used in the specification andin the claims, unless clearly indicated to the contrary, should beunderstood to mean “at least one.” The phrase “and/or,” as used in thespecification and in the claims, should be understood to mean “either orboth” of the elements so conjoined, i.e., elements that areconjunctively present in some cases and disjunctively present in othercases. Multiple elements listed with “and/or” should be construed in thesame fashion, i.e., “one or more” of the elements so conjoined. Otherelements may optionally be present other than the elements specificallyidentified by the “and/or” clause, whether related or unrelated to thoseelements specifically identified. Thus, as a non-limiting example, areference to “A and/or B”, when used in conjunction with open-endedlanguage such as “comprising” can refer, in one embodiment, to A only(optionally including elements other than B); in another embodiment, toB only (optionally including elements other than A); in yet anotherembodiment, to both A and B (optionally including other elements); etc.

As used in the specification and in the claims, “or” should beunderstood to have the same meaning as “and/or” as defined above. Forexample, when separating items in a list, “or” or “and/or” shall beinterpreted as being inclusive, i.e., the inclusion of at least one, butalso including more than one, of a number or list of elements, and,optionally, additional unlisted items. Only terms clearly indicated tothe contrary, such as “only one of” or “exactly one of,” or, when usedin the claims, “consisting of,” will refer to the inclusion of exactlyone element of a number or list of elements. In general, the term “or”as used shall only be interpreted as indicating exclusive alternatives(i.e. “one or the other but not both”) when preceded by terms ofexclusivity, such as “either,” “one of,” “only one of,” or “exactly oneof.” “Consisting essentially of,” when used in the claims, shall haveits ordinary meaning as used in the field of patent law.

As used in the specification and in the claims, the phrase “at leastone,” in reference to a list of one or more elements, should beunderstood to mean at least one element selected from any one or more ofthe elements in the list of elements, but not necessarily including atleast one of each and every element specifically listed within the listof elements and not excluding any combinations of elements in the listof elements. This definition also allows that elements may optionally bepresent other than the elements specifically identified within the listof elements to which the phrase “at least one” refers, whether relatedor unrelated to those elements specifically identified. Thus, as anon-limiting example, “at least one of A and B” (or, equivalently, “atleast one of A or B,” or, equivalently “at least one of A and/or B”) canrefer, in one embodiment, to at least one, optionally including morethan one, A, with no B present (and optionally including elements otherthan B); in another embodiment, to at least one, optionally includingmore than one, B, with no A present (and optionally including elementsother than A); in yet another embodiment, to at least one, optionallyincluding more than one, A, and at least one, optionally including morethan one, B (and optionally including other elements); etc.

The use of “including,” “comprising,” “having,” “containing,”“involving,” and variations thereof, is meant to encompass the itemslisted thereafter and additional items.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another or thetemporal order in which acts of a method are performed. Ordinal termsare used merely as labels to distinguish one claim element having acertain name from another element having a same name (but for use of theordinal term), to distinguish the claim elements.

Having thus described several aspects of at least one embodiment of thisinvention, it is to be appreciated that various alterations,modifications, and improvements will readily occur to those skilled inthe art. Such alterations, modifications, and improvements are intendedto be part of this disclosure, and are intended to be within the spiritand scope of the invention. Accordingly, the foregoing description anddrawings are by way of example only.

What is claimed is:
 1. A method for linearizing frequency chirp in afrequency-modulated continuous wave (FMCW) coherent LiDAR system, themethod comprising: generating a continuous wave laser signal having afrequency characteristic, the frequency characteristic comprising afrequency chirp over a frequency band in at least one period; receivinga signal based on the generated laser signal, wherein the receivedsignal is a reflected signal from a reference reflector positionedexternal to the LiDAR system, wherein the reference reflector ispositioned at a pre-determined, fixed range from the LiDAR system;mixing the received signal with a local oscillator signal, the localoscillator signal having the frequency characteristic; determining atleast one beat frequency based on the mixed signal; sampling the mixedsignal at a rate equal to at least two times the beat frequency; anddetermining a correction signal based on the sampled signal and on thepre-determined, fixed range from the LiDAR system to the referencereflector.
 2. The method of claim 1, wherein determining at least onebeat frequency of the mixed signal comprises determining a maximum beatfrequency, and wherein sampling the mixed signal is at a rate equal toat least two times the maximum beat frequency.
 3. The method of claim 1,further comprising scanning the reference reflector with the generatedlaser signal.
 4. The method of claim 1, wherein, for a given sample inthe sampled signal, the correction signal indicates a difference betweenthe laser signal and an ideal signal.
 5. The method of claim 1, furthercomprising: determining at least one of a range or a velocity of atarget based on the reflected correction signal.
 6. The method of claim1, wherein the continuous wave laser signal having the frequencycharacteristic is a first continuous wave laser signal, and wherein themethod further comprises applying the correction signal to a secondcontinuous wave laser signal.
 7. The method of claim 6, wherein applyingthe correction signal to the second continuous wave laser signalcomprises: providing the correction signal to a modulator coupled to alaser, the laser configured to generate the second continuous wave lasersignal.
 8. A method for linearizing frequency chirp in afrequency-modulated continuous wave (FMCW) coherent LiDAR system, themethod comprising: generating a continuous wave laser signal having afrequency characteristic, the frequency characteristic comprising afrequency chirp over a frequency band in at least one period; receivinga signal based on the generated laser signal, wherein the receivedsignal is a reflected signal from a reference reflector positionedexternal to the LiDAR system; mixing the received signal with a localoscillator signal, the local oscillator signal having the frequencycharacteristic; determining at least one beat frequency based on themixed signal; sampling the mixed signal at a rate equal to at least twotimes the beat frequency; and determining a correction signal based onthe sampled signal, wherein, for a given sample in the sampled signal,the correction signal indicates a difference between the laser signaland an ideal signal, wherein the ideal signal has an ideal frequencycharacteristic, the ideal frequency characteristic comprising a linearfrequency chirp over the frequency band in the at least one period, andwherein the difference is between the frequency characteristic of thelaser signal and the ideal frequency characteristic.
 9. The method ofclaim 8, wherein the linear frequency chirp comprises a first linearchirp having a positive slope and a second linear chirp having anegative slope.
 10. The method of claim 8, determining the correctionsignal based on the sampled signal comprises: determining an averagefrequency of the sampled signal; and determining the ideal signal basedthe average frequency.
 11. A system for linearizing frequency chirp in afrequency-modulated continuous wave (FMCW) coherent LiDAR system, thesystem comprising: a laser configured to generate a continuous wavelaser signal having a frequency characteristic, the frequencycharacteristic comprising a frequency chirp over a frequency band in atleast one period; a mixer coupled to an output of the laser andconfigured to mix: a received signal based on the generated lasersignal, wherein the received signal is a reflected signal from areference reflector positioned external to the LiDAR system, wherein thereference reflector is positioned at a pre-determined, fixed range fromthe LiDAR system; and a local oscillator signal having the frequencycharacteristic; an analog-to-digital converter coupled to an output ofthe mixer and configured to sample the mixed signal at a rate equal toat least two times a beat frequency of the mixed signal; and a processorcoupled to an output of the converter and configured to determine acorrection signal based on the sampled signal and on the pre-determined,fixed range from the LiDAR system to the reference reflector.
 12. Thesystem of claim 11, wherein the beat frequency is a maximum beatfrequency and wherein the converter is configured to sample the mixedsignal at a rate equal to at least two times the maximum beat frequency.13. The system of claim 11, further comprising: a scanner configured toscan the reference reflector or a target with the generated lasersignal.
 14. The system of claim 13, wherein the mixer is configured toreceive the reflected signal from the scanner, and wherein the reflectedsignal is based on a scan of the reference reflector.
 15. The system ofclaim 11, wherein, for a given sample in the sampled signal, thecorrection signal indicates a difference between the laser signal and anideal signal.
 16. The system of claim 11, further comprising a modulatorcoupled to the laser and configured to apply the correction signal tothe laser.
 17. A system for linearizing frequency chirp in afrequency-modulated continuous wave (FMCW) coherent LiDAR system, thesystem comprising: a laser configured to generate a continuous wavelaser signal having a frequency characteristic, the frequencycharacteristic comprising a frequency chirp over a frequency band in atleast one period; a mixer coupled to an output of the laser andconfigured to mix: a received signal based on the generated lasersignal, wherein the received signal is a reflected signal from areference reflector positioned external to the LiDAR system; and a localoscillator signal having the frequency characteristic; ananalog-to-digital converter coupled to an output of the mixer andconfigured to sample the mixed signal at a rate equal to at least twotimes a beat frequency of the mixed signal; and a processor coupled toan output of the converter and configured to determine a correctionsignal based on the sampled signal, wherein for a given sample in thesampled signal, the correction signal indicates a difference between thelaser signal and an ideal signal, wherein the ideal signal has an idealfrequency characteristic, the ideal frequency characteristic comprisinga linear frequency chirp over the frequency band in the at least oneperiod, and wherein the difference is between the frequencycharacteristic of the laser signal and the ideal frequencycharacteristic.
 18. The system of claim 17, wherein the linear frequencychirp comprises a first linear chirp having a positive slope and asecond linear chirp having a negative slope.
 19. The system of claim 17,wherein the processor is further configured to: determine an averagefrequency of the sampled signal; and determine the ideal signal basedthe average frequency.